cmaes_optimizer_sphere_function_minimization_quickstart.py

1import numpy as np
2from cmaes import CMA
3
4def objective(x):
5    return np.sum(x**2)
6
7def main():
8    optimizer = CMA(mean=np.zeros(2), sigma=1.3)
9
10    for generation in range(50):
11        solutions = []
12        for _ in range(optimizer.population_size):
13            x = optimizer.ask()
14            value = objective(x)
15            solutions.append((x, value))
16            print(f"#{generation} {value} (x1={x[0]}, x2={x[1]})")
17        optimizer.tell(solutions)
18
19if __name__ == "__main__":
20    main()